Project Summary A central question in biology is, How do populations of cells execute rapid, reproducible, and coordinated responses despite variability in gene expression across isogenic cells? One way that cells coordinate responses to environmental cues is through intermediate extracellular signals that are secreted and sensed by the cells; but because most studies of secreted extracellular signals are in cell populations, it is not known if these signals are produced uniformly or vary at a single-cell level. Recent studies of the toll-like receptor (TLR)-induced inflammatory response?completed by the applicants' lab and others?strongly support a new regulatory motif by which this response is coordinated by subsets of heterogeneously secreting cells that dynamically reprogram the population. The objective of this proposal is to dissect the mechanisms of this novel regulatory motif in TLR-stimulated macrophages. The central hypothesis is that subset(s) of `first responder' cells that are regulated by differences in cell signaling state coordinate the inflammatory response via paracrine signaling to neighboring cells. The rationale for the proposed research is that understanding how paracrine communication between subsets of cells controls the overall inflammatory response will open up new therapeutic strategies that target the balance between these functional subsets to more specifically treat chronic inflammatory and autoimmune disorders linked to dysregulated TLR signaling. Guided by the preliminary data, the central hypothesis will be tested by pursuing three specific aims. In Aim 1, a novel assay to measure multiplexed secretion in single cells will be used to quantify cell-to-cell heterogeneity in secretion and to determine which inflammatory functions depend on paracrine communication; data-driven statistical models built from single-cell data sets will then be used to hypothesize and test regulatory relationships between extracellular signals. Aim 2 will use live-cell imaging of intracellular signaling dynamics in single cells to determine if cell state controls the range of observed inflammatory gene expression levels across individual cells. In Aim 3, a computational model of cell-cell communication fit to single-cell data will be used to explore the advantage of using diverse cell responses versus more homogeneous ones to coordinate the activation and resolution of the inflammatory response; model predictions will then be tested experimentally. The contribution of the proposed research will be to show that cell-cell communication between heterogeneous responder cells indeed represents a new regulatory motif for coordinating responses to external stimuli. The approach is innovative because it combines single-cell technologies to experimentally quantify signaling and secretion in individual cells with computational modeling to interpret these complex data sets. This research will be significant because it is expected that similar mechanisms of paracrine communication between heterogeneous cell subsets regulate higher-order cell behaviors in other biological contexts; hence the findings could have broad implications across many disease types.